lorey

#!/bin/bash

mkdir -p ./rs/

for semester in $(seq -f "%02g" 4 15); do
    wget -O ./rs/20${semester}_SS_aufgaben.pdf --user "rs" --password "rechner.strukturen" https://capp.itec.kit.edu/teaching/rs/ss${semester}/kl/aufgaben.pdf ;
    wget -O ./rs/20${semester}_WS_aufgaben.pdf --user "rs" --password "rechner.strukturen" https://capp.itec.kit.edu/teaching/rs/ws${semester}/kl/aufgaben.pdf ;
    wget -O ./rs/20${semester}_SS_loesung.pdf --user "rs" --password "rechner.strukturen" https://capp.itec.kit.edu/teaching/rs/ss${semester}/kl/loesung.pdf ;
    wget -O ./rs/20${semester}_WS_loesung.pdf --user "rs" --password "rechner.strukturen" https://capp.itec.kit.edu/teaching/rs/ws${semester}/kl/loesung.pdf ;
done

lorey

# adapted from http://stackoverflow.com/a/25251803
profile = webdriver.FirefoxProfile()
profile.set_preference('browser.download.folderList', 2)  # custom location
profile.set_preference('browser.download.manager.showWhenStarting', False)
profile.set_preference('browser.helperApps.neverAsk.saveToDisk', 'text/vcard')  # type of file to download

# use the out folder of the script path
profile.set_preference('browser.download.dir', os.path.join(os.path.dirname(os.path.abspath(__file__)), 'out'))

lorey

import os

import pandas as pd
import psycopg2
from dotenv import find_dotenv
from dotenv import load_dotenv
from psycopg2.extras import DictCursor


def main():

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from bs4 import BeautifulSoup
from markdown import markdown
import re

def markdown_to_text(markdown_string):
    """ Converts a markdown string to plaintext """

    # md -> html -> text since BeautifulSoup can extract text cleanly
    html = markdown(markdown_string)

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from pandas.io.json import json_normalize
df = json_normalize(data)

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# this snippet will deal with errors like HTTPSConnectionPool: Max retries exceeded with url...
# by using a backoff factor
# further reading:
# - docs: https://2.python-requests.org/en/master/user/advanced/#transport-adapters
# - stack overflow issue: https://stackoverflow.com/a/47475019
import requests
from requests.adapters import HTTPAdapter
from requests.packages.urllib3.util.retry import Retry

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def hierarchical_to_flattened_parameters(parameters_dict):
    """
    Flatten an hierarchical dict to an sklearn parameter set.
    :param parameters_dict: hierarchical dict
    :return: flattened dict
    """
    return json_normalize(parameters_dict, sep='__').to_dict(orient='records')[0]

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# say we want to delete all files that contain the string "trash"
# source: https://stackoverflow.com/a/4529138

# 1) create a file that lists all files to delete
find .cache/ | xargs grep -l "trash" | awk '{print "rm "$1}' > delete.sh

# 2) check for errors and stuff
vim delete.sh

# 3) make the file executable and execute

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//
// This will hide all messages from a specific user in Slack. Enjoy the silence.
//

// get the owner id of a message
// -> loops back through list to find owner
function getOwnerId(i) {
  var current = i
  var sender = current.querySelector(".c-message__sender_link");
  var ownerId = sender ? sender.dataset.messageSender : null;

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#
# This small example shows you how to access JS-based requests via Selenium
# Like this, one can access raw data for scraping, 
# for example on many JS-intensive/React-based websites
#

from time import sleep

from selenium import webdriver
from selenium.webdriver import DesiredCapabilities